Project description:Non-small-cell lung cancer (NSCLC) accounts for more than 80 % of lung cancer cases. Epidermal growth factor receptor mutations (EGFRm) occur in 15 % and 40 % of NSCLC in Western and Asian populations, respectively. Current treatment for advanced NSCLC targets EGFRm with tyrosine kinase inhibitors (TKIs). Osimertinib is a third generation EGFR-TKI now used as a first-line treatment in advanced/metastatic NSCLC, however drug resistance frequently develops. Dysregulation of metabolism has been suggested to play a role in development of drug resistance. Here, we investigated the role of lipid metabolism in the development of osimertinib resistance (OR) using pharmacologically-induced resistant cellular models. We used a multi-omics approach, combining lipidomics with proteomics analyses. We found alterations in processes relating to metabolism, including dysregulated sphingolipid metabolism, lipid peroxidation and ferroptosis. In particular, we identified that OR lines reduce free ceramides in favour of complex glycosphingolipids. Mechanistically, this metabolic shift avoids ceramide-mediated apoptosis via caspase 3 activation. Importantly, when we combined osimertinib with D-PDMP, an inhibitor of the key enzyme responsible for the conversion of ceramide to glucosylceramide, we increased sensitivity to osimertinib. Overall, we have identified the glycosphingolipid metabolic pathway as a potential therapeutic target to reinstate sensitivity to osimertinib in NSCLC.
Project description:We report a detailed characterization of the HPV16 genome in two brain metastases from OPSCC tumors. The use of a target enrichment strategy followed by next generation sequencing (NGS) provided an effective way to identify viral infection in tumor genome, including internal deletions and insertion sites into the host genome. Applying similar strategies to a larger cohort of HPV+ HNSCC brain metastases could help to identify biomarkers that can predict metastasis and/or identify novel therapeutic options.
Project description:Lung cancer is the leading cause of cancer-related death worldwide, and non-small cell lung cancer (NSCLC) accounts for approximately 85% of lung cancers. Lymphatic metastasis serves as a predominant NSCLC metastatic route and an essential predictor of patient prognosis. Recently, circular RNA (circRNA) has emerged as critical mediator in various tumor initiation and progression. To identify essential circRNA that involves in the lymphatic metastasis of NSCLC, Next generation sequencing (NSG) was performed in 6 paired NSCLC tissues and normal adjacent tissues (NAT).
Project description:The expression profiles of miRNAs in drug-resistant non-small cell lung cancer (NSCLC) cell lines were identified via next generation sequencing and the common dysregulated miRNAs in drug-resistant NSCLC cell lines were picked up for further analysis.
Project description:Most proteogenomic approaches for mapping single amino acid polymorphisms (SAPs) require construction of a sample-specific database containing protein variants predicted from the next-generation sequencing (NGS) data. We present a new strategy for direct SAP detection without relying on NGS data. Among the 348 putative SAP peptides identified in an industrial yeast strain, 85.6% of SAP sites were validated by genomic sequencing.